miRNA Target Prediction Algorithms Research Articles

Abstract 461: Dual-kinase targeted miRNA nanotherapy for the treatment of triple-negative breast cancer

Abstract Triple-negative breast cancer (TNBC) represents 20% of breast cancer (BC) patients (51,000 cases/year in the US). It is associated with a highly aggressive course, early metastasis and relapses, and drug-resistant phenotype. About 40% of the patients die within 5 years despite available therapies. If the disease is metastatic, patients survive only 13 months. Since TNBC does not express targetable receptors such as ER, PR, and HER2, and it is a highly heterogeneous cancer with six genetically defined sub-types, currently, there are no common actionable molecular targets and no effective targeted therapies for TNBC. microRNAs (miRNAs) are 18-20 nt long non-coding RNAs and are often dysregulated in cancer cells. Tumor-suppressive miRNAs specifically silence their protooncogenic target genes (mRNAs) by binding specifically to their 3’-UTRs located in their target mRNAs, leading to inhibition of oncogenes that play critical roles in cell proliferation, cell cycle, migration, invasion, angiogenesis, drug resistance, tumor growth, and progression. We have previously demonstrated that Eukaryotic Elongation factor-2 kinase (eEF2K) and AXL are oncogenic kinases, and their higher expression is associated with poor survival in patients with TNBC. However, currently, there is no FDA-approved eEF2K and AXL-targeted therapeutics. To effectively co-target these kinases, we extensively analyzed miRNA databases using miRNA target prediction algorithms and recently, we discovered that miR-329-3p has a specific binding site at both 3’-UTRs of eEF2K and AXL mRNAs. Analyzing the TCGA TNBC database, we found that low expression of miR-329-3p is correlated with shorter overall survival in TNBC patients, and the expression of miR-329-3p is commonly reduced or lost in TNBC patient tumors. Since the successful clinical application of miRNA-based therapeutics requires safe and effective nano-delivery systems, we have developed magnetic iron-oxide-based nanoparticles (MNPs) for the delivery of miR-329-3p. We showed that miR-329-3p significantly suppresses cell proliferation, invasion, and migration by targeting both eEF2K and AXL and their downstream mediators such as SRC/FAK and Cyclin D1 in TNBC cell lines. In vivo systemic treatment with MNPs-miR-329 completely blocks tumor growth in orthotopic MDA-MB-231 and MDA-MB-436 TNBC xenograft models in mice. Analysis of tumors shows remarkable inhibition in eEF2K and AXL expression, and clinically significant downstream targets including SRC, FAK, and Cyclin D1. We also demonstrated that miR-329 nanotherapy induces apoptosis and inhibits intratumoral proliferation in TNBC tumors in mice. Toxicity markers in mouse blood samples show that miR-329 nanotherapy is safe and not toxic to mice. Taken together, our study suggests that miR-329-3p nanotherapy may be used as a novel potential therapeutic approach in TNBC patients. Citation Format: Goknur Kara, Pinar Atalay Dundar, Nermin Kahraman, Emir Baki Denkbas, Bulent Ozpolat. Dual-kinase targeted miRNA nanotherapy for the treatment of triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 461.

DIANA-microT 2023: including predicted targets of virally encoded miRNAs.

DIANA-microT-CDS is a state-of-the-art miRNA target prediction algorithm catering the scientific community since 2009. It is one of the first algorithms to predict miRNA binding sites in both the 3' Untranslated Region (3'-UTR) and the coding sequence (CDS) of transcripts, with increased performance. Its current version, DIANA-microT 2023 (www.microrna.gr/microt_webserver/), brings forward a significantly updated set of interactions. DIANA-microT-CDS has been executed utilizing annotation information from Ensembl v102, miRBase 22.1 and, for the first time, MirGeneDB 2.1, yielding more than 83 million interactions in human, mouse, rat, chicken, fly and worm species. Additionally, this version delivers predicted interactions of miRNAs encoded from 20 viruses against host transcripts from human, mouse and chicken species. Numerous resources have been interconnected into DIANA-microT, including DIANA-TarBase, plasmiR, HMDD, UCSC, dbSNP, ClinVar, as well as miRNA/gene abundance values for 369 distinct cell-lines/tissues. The server interface has been redesigned allowing users to use smart filtering options, identify abundance patterns of interest, pinpoint known SNPs residing on binding sites and obtain miRNA-disease information. The contents of DIANA-microT webserver are freely accessible and can also be locally downloaded without any login requirements.

MiRBind: A Deep Learning Method for miRNA Binding Classification

The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To date, the potential for miRNA:target site binding is evaluated using either co-folding free energy measures or heuristic approaches, based on the identification of binding 'seeds', i.e., continuous stretches of binding corresponding to specific parts of the miRNA. The limitations of both these families of methods have produced generations of miRNA target prediction algorithms that are primarily focused on 'canonical' seed targets, even though unbiased experimental methods have shown that only approximately half of in vivo miRNA targets are 'canonical'. Herein, we present miRBind, a deep learning method and web server that can be used to accurately predict the potential of miRNA:target site binding. We trained our method using seed-agnostic experimental data and show that our method outperforms both seed-based approaches and co-fold free energy approaches. The full code for the development of miRBind and a freely accessible web server are freely available.

LncRNA KCNQ1OT1 accelerates ovarian cancer progression via miR-125b-5p/CD147 axis.

Ovarian cancer (OC) is one of the most common gynecological malignancies with a high incidence. Researches showed that lncRNA KCNQ1OT1 (KCNQ1OT1) was involved various tumors progression, including OC. However, the precise mechanism of KCNQ1OT1 in OC needs to be further clarified. For investigate the underlying mechanism of KCNQ1OT1 regulating OC progression. CCK-8 assay, colony formation assay, Transwell assay, Western blot and quantitative real-time PCR (qRT-PCR) were performed to examine viability, proliferation, migration and invasion, genes and proteins' level. To identify KCNQ1OT1 as a regulator of miR-125b-5p and miR-125b-5p as a regulator of CD147, we used miRNA target prediction algorithms, Pearson's correlation analysis and dual-luciferase reporter gene assay. KCNQ1OT1 was high expression and miR-125b-5p was low expression in OC, and KCNQ1OT1 was negatively correlated with that of miR-125b-5p in OC specimens. KCNQ1OT1 promoted OC cell proliferation and metastasis by binding to miR-125b-5p. miR-125b-5p targeted CD147, and which was negatively correlated with that of miR-125b-5p in OC specimens. KCNQ1OT1 was positively correlated with that of CD147 in OC specimens, and KCNQ1OT1 accelerated OC progression via miR-125b-5p/CD147 axis. KCNQ1OT1 accelerated OC progression via miR-125b-5p/CD147 axis indicating KCNQ1OT1 serve as a novel biomarker for OC treatment. Our research provides a new direction for OC treatment.

The Oncogenic and Tumor Suppressive Long Non-Coding RNA-microRNA-Messenger RNA Regulatory Axes Identified by Analyzing Multiple Platform Omics Data from Cr(VI)-Transformed Cells and Their Implications in Lung Cancer.

Chronic exposure to hexavalent chromium (Cr(VI)) causes lung cancer in humans, however, the underlying mechanism has not been well understood. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are commonly studied non-coding RNAs. miRNAs function mainly through interaction with the 3′-untranslated regions of messenger RNAs (mRNAs) to down-regulate gene expression. LncRNAs have been shown to function as competing endogenous RNAs (ceRNAs) to sponge miRNAs and regulate gene expression. It is now well accepted that lncRNAs and miRNAs could function as oncogenes or tumor suppressors. Dysregulations of lncRNAs and miRNAs have been shown to play important roles in cancer initiation, progression, and prognosis. To explore the mechanism of Cr(VI) lung carcinogenesis, we performed lncRNA, mRNA, and miRNA microarray analysis using total RNAs from our previously established chronic Cr(VI) exposure malignantly transformed and passage-matched control human bronchial epithelial BEAS-2B cells. Based on the differentially expressed lncRNAs, miRNAs, and mRNAs between the control (BEAS-2B-Control) and Cr(VI)-transformed (BEAS-Cr(VI)) cells and by using the lncRNA–miRNA interaction and miRNA target prediction algorithms, we identified three oncogenic (HOTAIRM1/miR-182-5p/ERO1A, GOLGA8B/miR-30d-5p/RUNX2, and PDCD6IPP2/miR-23a-3p/HOXA1) and three tumor suppressive (ANXA2P1/miR-20b-5p/FAM241A (C4orf32), MIR99AHG/miR-218-5p/GPM6A, and SH3RF3-AS1/miR-34a-5p/HECW2) lncRNA–miRNA–mRNA regulatory axes. Moreover, the relevance of these three oncogenic and three tumor suppressive lncRNA–miRNA–mRNA regulatory axes in lung cancer was explored by analyzing publicly available human lung cancer omics datasets. It was found that the identified three oncogenic lncRNA–miRNA–mRNA regulatory axes (HOTAIRM1/miR-182-5p/ERO1A, GOLGA8B/miR-30d-5p/RUNX2, and PDCD6IPP2/miR-23a-3p/HOXA1) and the three tumor suppressive lncRNA–miRNA–mRNA regulatory axes (ANXA2P1/miR-20b-5p/FAM241A (C4orf32), MIR99AHG/miR-218-5p/GPM6A, and SH3RF3-AS1/miR-34a-5p/HECW2) have significant diagnostic and prognosis prediction values in human lung cancer. In addition, our recent studies showed that Cr(VI)-transformed cells display cancer stem cell (CSC)-like properties. Further bioinformatics analysis identified the oncogenic lncRNA–miRNA–mRNA regulatory axes as the potential regulators of cancer stemness. In summary, our comprehensive analysis of multiple platform omics datasets obtained from Cr(VI)-transformed human bronchial epithelial cells identified several oncogenic and tumor suppressive lncRNA–miRNA–mRNA regulatory axes, which may play important roles in Cr(VI) carcinogenesis and lung cancer in general.

MiRNA-193b-5p Suppresses Pancreatic Cancer Cell Proliferation, Invasion, Epithelial Mesenchymal Transition, and Tumor Growth by Inhibiting eEF2K.

Pancreatic ductal adenocarcinoma (PDAC) is the 4th leading cause of cancer deaths in the US due to the lack of effective targeted therapeutics and extremely poor prognosis. The study aims to investigate the role of miR-193b and related signaling mechanisms in PDAC cell proliferation, invasion, and tumor growth. Using PDAC cell lines, we performed cell viability, colony formation, in vitro wound healing, and matrigel invasion assays following transfection with miR-193b mimic or control-miR. To identify potential downstream targets of miR-193b, we utilized miRNA-target prediction algorithms and investigated the regulation of eukaryotic elongation factor-2 kinase (eEF2K) and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signaling pathways and mediators of epithelial mesenchymal transition (EMT). The role of miR-193b in PDAC tumorigenesis was evaluated in in vivo tumor growth of Panc-1 xenograft model in nude mice. We found that miR-193b is under expressed in PDAC cells compared to corresponding normal pancreatic epithelial cells and demonstrated that ectopic expression of miR-193b reduced cell proliferation, migration, invasion, and EMT through downregulation of eEF2K signaling in PDAC cells. miR-193b expression led to increased expression of E-Cadherin and Claudin-1 while decreasing Snail and TCF8/ZEB1 expressions via eEF2K and MAPK/ERK axis. In vivo systemic injection of miR-193b using lipid-nanoparticles twice a week reduced tumor growth of Panc-1 xenografts and eEF2K expression in nude mice. Our findings suggest that miR-193b expression suppresses PDAC cell proliferation, migration, invasion, and EMT through inhibition of eEF2K/MAPK-ERK oncogenic axis and that miR-193b-based RNA therapy might be an effective therapeutic strategy to control the growth of PDAC.

Comparative transcriptome analysis of miRNA in hydronephrosis male children caused by ureteropelvic junction obstruction with or without renal functional injury.

MicroRNAs (miRNAs or miRs) are non-coding RNAs that contribute to pathological processes of various kidney diseases. Renal function injury represents a final common outcome of congenital obstructive nephropathy and has attracted a great deal of attention. However the molecular mechanisms are still not fully established. In this study, we compared transcriptome sequencing data of miRNAs of renal tissues from congenital hydronephrosis children with or without renal functional injury, in order to better understand whether microRNAs could play important roles in renal functional injury after ureteropelvic junction obstruction. A total of 22 microRNAs with significant changes in their expression were identified. Five microRNAs were up-regulated and 17 microRNAs were down-regulated in the renal tissues of the hydronephrosis patients with renal function injury compared with those without renal function injury. MicroRNA target genes were predicted by three major online miRNA target prediction algorithms, and all these mRNAs were used to perform the gene ontology analysis and Kyoto Encyclopedia of Gene and Genomes pathway analysis. Then, twelve candidate human and rat homologous miRNAs were selected for validation using RT-qPCR in vitro and in vivo; only miR-187-3p had a trend identical to that detected by the sequencing results among the human tissues, in vivo and in vitro experimental models. In addition, we found that the change of miR-187-3p in vivo was consistent with results in vitro models and showed a decrease trend in time dependence. These results provided a detailed catalog of candidate miRNAs to investigate their regulatory role in renal injury of congenital hydronephrosis, indicating that they may serve as candidate biomarkers or therapeutic targets in the future.

Identification of tRNA-derived Fragments and Their Potential Roles in Atherosclerosis

Atherosclerosis (AS), a chronic inflammatory disease, is the basis of cardiovascular disease (CVD). Although the treatment has been greatly improved, AS still imposes a large burden on human health and the medical system, and we still need to further study its pathogenesis. As a novel biomolecule, transfer RNA-derived fragments (tRFs) play a key role in the progression of various disease. However, whether tRFs contribute to atherosclerosis pathogenesis remains unexplored. With deep sequencing technology, the change of tRFs expression profiles in patients with AS compared to healthy control group was identified. The accuracy of the sequencing data was validated using RT qPCR. Subsequently, we predicted the potential target genes of tRFs by online miRNA target prediction algorithms. The potential functions of tRFs were evaluated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. There were 13 tRFs differentially expressed between patients with AS and healthy controls, of which 2 were up-regulated and 11 were down-regulated. Validation by RT-qPCR analysis confirmed the sequencing results, and tRF-Gly-GCC-009 was highly up-regulated in the AS group based on the results of sequencing which was confirmed by RT-qPCR analysis. Furthermore, GO enrichment and KEGG pathway analyses indicated that 10 signaling pathways were related to tRF-Gly-GCC-009. These pathways might be physiopathological fundamentals of AS, mainly involving in Apelin signaling, Notch signaling and calcium signaling. The results of our study provide important novel insight into the underlying pathogenesis and demonstrate that tRFs might be potential biomarkers and therapeutic targets for AS in the future.

Targeting of Marcks By MiR-34a Overcomes Drug Resistance in Multiple Myeloma

Multiple myeloma (MM) is a plasma cell malignancy characterized by abnormal proliferation of clonal plasma cells in the bone marrow. Current therapies, such as the proteasome inhibitor bortezomib (BTZ), have improved the outcome of patients. Nevertheless MM remains an incurable disease with a high rate of relapse and development of drug resistance. So far, the pathogenic mechanisms underlying drug resistance of MM are not fully elucidated. Our previous study showed the overexpression of MARCKS (Myristoylated alanine-rich C-kinase substrate) protein in MM cells played an important role in drug resistance. However; the mechanism (s) underlying MARCKS overexpression and its association with drug resistance in MM have not been elucidated.In the current study, to investigate whether miRNAs play a role in aberrant upregulation of MARCKS in drug resistance, several miRNA-target prediction algorithms were exploited to generate a selective miRNA library for subsequent screening. Among 52 miRNA candidates that target MARCKS, the expression level of several miRNAs with higher score was assessed in drug resistant cell lines (8226-R5 and MM1.R) in comparison to the parental cells (8226 and MM1.S). We observed that miR-34a expression was most significantly downregulated in 8226-R5 and MM1.R cell lines relative to their parental lines, 8226 and MM1S. We also identified a negative correlation between MARCKS and miR-34a expression levels in 6 primary patient samples and two healthy donor samples. Next, to confirm direct targeting of MARCKS by miR-34a, two MM resistant cell lines (8226-R5 and MM1R) were transduced with lentiviral vectors harboring miR-34a precursor gene or scramble control and mRNA and protein level of MARCKS were assessed in miR-34a overexpressing cell lines in comparison to scramble control. Overexpression of miR-34a reduced MARCKS expression level in both mRNA and protein levels. In addition, the luciferase reporter assay was performed to validate MARCKS as a direct target of miR-34a. To this end, the 3' UTR sequence of human MARCKS was cloned into the luciferase-expressing vector pEZX-MT01 to the downstream of the firefly luciferase gene. Co-transfection of MARCKS-UTR or negative control luciferase reporter vectors together with miR-34a expressing or control vector showed that miR-34a overexpression significantly reduced the luciferase activity, indicating that miR-34a can directly target the MARCKS 3′ UTR.To examine the functional effect of miR-34a on cell proliferation and apoptosis in MM cells, the miR-34a overexpressing or scramble control cell lines were treated with BTZ. Overexpression of miR-34a in drug resistant cell lines re-sensitized them to BTZ. Furthermore, FACS analysis revealed that overexpression of miR-34a could induce apoptosis in drug resistant MM cell lines as indicated by an increase in the percentage of annexin-V positive cells compared to the control, suggesting that downregulation of miR-34a is associated with acquired BTZ-resistance in MM.To further elucidate the interaction of miR-34a and MARCKS, we knocked down MARCKS expression by transfecting shMARCKS lentiviral vector into 8226-R5 and MM1.R resistant cell lines and examined the miR-34a level in MARCKS-knockdown cells. We found that miR-34a is also regulated by MARCKS as silencing of MARCKS could restore the miR-34a expression level in MM resistant cell lines. In compatible with miR-34a overexpression experiments, following the knockdown of MARCKS, both cell lines had significantly lower viability after treatment with BTZ, in comparison to negative controls. We also showed that knockdown of MARCKS by shMARCKS silencing or suppression of MARCKS by miR-34a overexpression increased the mRNA and protein levels of some pro-apoptotic genes including PUMA which may be involved in induction of apoptosis in drug resistant MM cells.In conclusion, our data indicate that miR-34a is downregulated in drug resistant MM cell lines and primary MM cells, which contributes to the drug resistance of MM through upregulation of MARCKS. Moreover, regulatory interaction between miR-34a and MARCKS provides the rationale that restoration of miR-34a may serve as a promising therapeutic approach by targeting MARCKS in patients with refractory/relapsed MM. DisclosuresNo relevant conflicts of interest to declare.

Genomic Profiling and Functional Analysis of let-7c miRNA-mRNA Interactions Identify SOX13 to Be Involved in Invasion and Progression of Pancreatic Cancer.

Background Pancreatic cancer is a devastating disease; its lethality is related to rapid growth and tendency to invade adjacent organs and metastasize at an early stage. Objective The aim of this study was to identify miRNAs and their gene targets involved in the invasive phenotype in pancreatic cancer to better understand the biological behaviour and the rapid progression of this disease. Methods miRNA profiling was performed in isogenic matched high invasive and low-invasive subclones derived from the MiaPaCa-2 cell line and validated in a panel of pancreatic cancer cell lines, tumour, and normal pancreas. Online miRNA target prediction algorithms and gene expression arrays were used to predict the target genes of the differentially expressed miRNAs. miRNAs and potential target genes were subjected to overexpression and knockdown approaches and downstream functional assays to determine their pathological role in pancreatic cancer. Results Differential expression analysis revealed 10 significantly dysregulated miRNAs associated with invasive capacity (Student's t-tests; P value <0.05; fold change = ±2). The expression of top upregulated miR-135b and downregulated let-7c miRNAs correlated with the invasive abilities of eight pancreatic cancer cell lines and displayed differential expression in pancreatic cancer and adjacent normal tissue specimens. Ectopic overexpression of let-7c decreased proliferation, invasion, and colony formation. Integrated analysis of miRNA-mRNA using in silico algorithms and experimental validation databases identified four putative gene targets of let-7c. One of these targets, SOX13, was found to be upregulated in PDAC tumour compared with normal tissue in TCGA and an independent data set by qPCR and immunohistochemistry. RNAi knockdown of SOX13 reduced the invasion and colony formation ability of pancreatic cancer cells. Conclusion The identification of key miRNA-mRNA gene interactions and networks provide potential diagnostic and therapeutic strategies for better treatment options for pancreatic cancer patients.

Therapeutic potential of miRNAs targeting SARS-CoV-2 host cell receptor ACE2

In late December 2019, several cases of pneumonia of unknown etiology (COVID-19) were reported in Wuhan, Hubei province, China. Based on clinical findings, blood tests and chest radiographs, this disease was diagnosed as a virus-associated pneumonia. Sequence analysis revealed a novel coronavirus, called SARS-CoV-2 (formerly called 2019-nCoV), as the causative agent of pneumonia of unknown etiology. So far, the SARS-CoV-2 infection continues to spread, and this virus poses a serious public health threat. In this study, it was aimed to reveal potential miRNA targets for the regulation of SARS-CoV-2 host cell receptor ACE2. For the identification of potential miRNA targets for the ACE2 gene, TarBase v.8 (DIANA Tools), TargetScan, miRTarBase and miRDB miRNA-target prediction algorithms were used. FANTOM5 CAGE was used for the cellular ontology analysis. Expression levels of these miRNAs were determined using OncomiR Pan-Cancer miRNome Atlas. The results suggest that members of miR-200 family of miRNAs, especially miR-200c-3p, are strong candidate targets for the regulation of ACE2 in respiratory system cells. Consequently, the present study for the first time emphasizes potential use of miRNA-based therapeutics in the battle against SARS-CoV-2 infection and its deadly disease, COVID-19.

Integrative Proteomic and MicroRNA Analysis: Insights Into Mechanisms of Eyestalk Ablation-Induced Ovarian Maturation in the Swimming Crab Portunus trituberculatus.

Eyestalk ablation is the most common method to induce ovarian maturation in decapod crustacean aquaculture, but it jeopardizes broodstock survival and larvae production. It is important to understand the molecular basis underlying the maturation triggered by ablation and thereby develop an alternative measure for maturation manipulation. In this study, we investigate alterations of ovarian proteome and miRNA profile after ablation in a commercially important marine crab Portunus trituberculatus. Quantitative proteomic analysis using iTRAQ reveals that 163 proteins are differentially expressed following ablation, and modulation of methyl farnesoate metabolism and activation of calcium signaling may play important roles in the ovarian maturation induced by ablation. miRNA expression profiling identifies 31 miRNAs that show statistically significant changes. Integration of miRNA and proteome expression data with miRNA target prediction algorithms generates a potential regulatory network consisting of 26 miRNAs and 30 proteins linked by 71 possible functional associations. The miRNA-protein network analysis suggests that miRNAs are involved in promoting ovarian maturation by controlling expression of proteins related to methyl farnesoate synthesis, calcium signals, and energy metabolism. Experimental validation and temporal expression analysis indicate multiple miRNAs can act synergistically to regulate expression of Farnesoic acid O-methyltransferase and Calmodulin. Our findings provide new insights for elucidating the mechanisms underlying eyestalk ablation-induced ovarian maturation and could be useful for devising an alternative technique for manipulating reproduction in P. trituberculatus and other decapods.

MiRACLe: an individual-specific approach to improve microRNA-target prediction based on a random contact model.

Deciphering microRNA (miRNA) targets is important for understanding the function of miRNAs as well as miRNA-based diagnostics and therapeutics. Given the highly cell-specific nature of miRNA regulation, recent computational approaches typically exploit expression data to identify the most physiologically relevant target messenger RNAs (mRNAs). Although effective, those methods usually require a large sample size to infer miRNA-mRNA interactions, thus limiting their applications in personalized medicine. In this study, we developed a novel miRNA target prediction algorithm called miRACLe (miRNA Analysis by a Contact modeL). It integrates sequence characteristics and RNA expression profiles into a random contact model, and determines the target preferences by relative probability of effective contacts in an individual-specific manner. Evaluation by a variety of measures shows that fitting TargetScan, a frequently used prediction tool, into the framework of miRACLe can improve its predictive power with a significant margin and consistently outperform other state-of-the-art methods in prediction accuracy, regulatory potential and biological relevance. Notably, the superiority of miRACLe is robust to various biological contexts, types of expression data and validation datasets, and the computation process is fast and efficient. Additionally, we show that the model can be readily applied to other sequence-based algorithms to improve their predictive power, such as DIANA-microT-CDS, miRanda-mirSVR and MirTarget4. MiRACLe is publicly available at https://github.com/PANWANG2014/miRACLe.

Prediction of miRNA targets by learning from interaction sequences.

MicroRNAs (miRNAs) are involved in a diverse variety of biological processes through regulating the expression of target genes in the post-transcriptional level. So, it is of great importance to discover the targets of miRNAs in biological research. But, due to the short length of miRNAs and limited sequence complementarity to their gene targets in animals, it is challenging to develop algorithms to predict the targets of miRNA accurately. Here we developed a new miRNA target prediction algorithm using a multilayer convolutional neural network. Our model learned automatically the interaction patterns of the experiment-validated miRNA:target-site chimeras from the raw sequence, avoiding hand-craft selection of features by domain experts. The performance on test dataset is inspiring, indicating great generalization ability of our model. Moreover, considering the stability of miRNA:target-site duplexes, our method also showed good performance to predict the target transcripts of miRNAs.

MiRNA target identification and prediction as a function of time in gene expression data

ABSTRACT The understanding of miRNA target interactions is still limited due to conflicting data and the fact that high-quality validation of targets is a time-consuming process. Faster methods like high-throughput screens and bioinformatics predictions are employed but suffer from several problems. One of these, namely the potential occurrence of downstream (i.e. secondary) effects in high-throughput screens has been only little discussed so far. However, such effects limit usage for both the identification of interactions and for the training of bioinformatics tools. In order to analyse this problem more closely, we performed time-dependent microarray screening experiments overexpressing human miR-517a-3p, and, together with published time-dependent datasets of human miR-17-5p, miR-135b and miR-124 overexpression, we analysed the dynamics of deregulated genes. We show that the number of deregulated targets increases over time, whereas seed sequence content and performance of several miRNA target prediction algorithms actually decrease over time. Bioinformatics recognition success of validated miR-17 targets was comparable to that of data gained only 12 h post-transfection. We therefore argue that the timing of microarray experiments is of critical importance for detecting direct targets with high confidence and for the usability of these data for the training of bioinformatics prediction tools.

Position-wise binding preference is important for miRNA target site prediction.

It is a fundamental task to identify microRNAs (miRNAs) targets and accurately locate their target sites. Genome-scale experiments for miRNA target site detection are still costly. The prediction accuracies of existing computational algorithms and tools are often not up to the expectation due to a large number of false positives. One major obstacle to achieve a higher accuracy is the lack of knowledge of the target binding features of miRNAs. The published high-throughput experimental data provide an opportunity to analyze position-wise preference of miRNAs in terms of target binding, which can be an important feature in miRNA target prediction algorithms. We developed a Markov model to characterize position-wise pairing patterns of miRNA-target interactions. We further integrated this model as a scoring method and developed a dynamic programming (DP) algorithm, MDPS (Markov model-scored Dynamic Programming algorithm for miRNA target site Selection) that can screen putative target sites of miRNA-target binding. The MDPS algorithm thus can take into account both the dependency of neighboring pairing positions and the global pairing information. Based on the trained Markov models from both miRNA-specific and general datasets, we discovered that the position-wise binding information specific to a given miRNA would benefit its target prediction. We also found that miRNAs maintain region-wise similarity in their target binding patterns. Combining MDPS with existing methods significantly improves their precision while only slightly reduces their recall. Therefore, position-wise pairing patterns have the promise to improve target prediction if incorporated into existing software tools. The source code and tool to calculate MDPS score is available at http://hulab.ucf.edu/research/projects/MDPS/index.html. Supplementary data are available at Bioinformatics online.

Abstract P1-05-03: Phosphorylation of KAP1 Serine 473 regulates mitochondrial dynamics through miR-20b under metabolic stress in breast cancer

Abstract Cancer has been considered a metabolic disease in recent years. Compared to normal cells, cancer cells rewire metabolic pathways to sustain their outgrowth. While growing fast, cancer cells in the core region of a solid tumor encounter metabolic stress induced by hypoxia and insufficient nutrition, and mitochondrial dynamics has a profound effect on the survival of cancer cells. However, how mitochondrial dynamics affects cancer cell survival under metabolic stress has not been fully elucidated. Krüppel-associated box-associated protein-1 (KAP1), also known as TRIM28, is a transcriptional co-regulator participating in multiple cellular physiological processes. The post-translational modifications of KAP1 play an essential role in regulating its function. We have previously demonstrated that KAP1 mRNA is highly expressed in concomitant with the upregulation of genes involving in glycolysis and oxidative phosphorylation in breast cancer. Furthermore, KAP1 is phosphorylated at Serine 473 (pS473) upon the induction of nutrient stresses via reactive oxygen species (ROS)-p38 MAPK signaling in breast cancer cells. The S473 phosphorylation of KAP1 reduces the expression of mitochondrial outer membrane protein mitofusin 2 (MFN2), which prevents the hyperfusion of mitochondria and the overproduction of ROS under nutrient deprivation. However, the mechanism of how KAP1 regulates the expression of MFN2 remains unclear. We have engineered a KAP1-deficient MDA-MB-231 cell line and re-expressed KAP1 S473 wild-type (WT), S473A (phosphorylation-defective) or S473D (phosphorylation-mimic) mutants. By analyzing the mRNA expression profiles from these cell lines, several microRNAs (miRNAs) were shown to be upregulated in the KAP1 S473D-expressing cells, which implied that pS473-KAP1 may regulate MFN2 expression through miRNA. Using several miRNA target prediction algorithms, miR-20b was predicted to target the 3’-untranslated region (UTR) of MFN2 mRNA, and the sequence of target site was conserved through evolution. By performing MFN2 3’UTR dual luciferase reporter assays, we have confirmed that MFN2 3’UTRwas targeted by miR-20b and regulated by the phosphorylation status at S473 of KAP1. Also, miR-20b expression was upregulated upon glucose deprivation and both MFN2 mRNA and protein levels declined in breast cancercells overexpressed with miR-20b mimics. In addition, KAP1 S473D, rather than S473A-expressing cells produced more miR-20b under glucose depletion condition and MFN2 expression levels were inversely correlated with miR-20b expression. Moreover, the analysis of The Cancer Genome Atlas (TCGA) breast tumor datasets indicated that there was higher miR-20b but lower MFN2 expression in advanced breast tumors compared with the primary tumors and normal tissues. In conclusion, these results suggested that the induction of KAP1 S473 phosphorylation under nutrition deprivation inhibited MFN2 by upregulating miR-20b, which prevented mitochondrial hyperfusion and consequently benefited breast cancer cell survival in response to metabolic stress. Citation Format: Yu-Shu Liu, Chun-Ting Cheng, Ching Ouyang, Ge-Jyun Liu, David Kong Ann, Ching-Ying Kuo. Phosphorylation of KAP1 Serine 473 regulates mitochondrial dynamics through miR-20b under metabolic stress in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-05-03.

FilTar: using RNA-Seq data to improve microRNA target prediction accuracy in animals.

MotivationMicroRNA (miRNA) target prediction algorithms do not generally consider biological context and therefore generic target prediction based on seed binding can lead to a high level of false-positive predictions. Here, we present FilTar, a method that incorporates RNA-Seq data to make miRNA target prediction specific to a given cell type or tissue of interest.ResultsWe demonstrate that FilTar can be used to: (i) provide sample specific 3′-UTR reannotation; extending or truncating default annotations based on RNA-Seq read evidence and (ii) filter putative miRNA target predictions by transcript expression level, thus removing putative interactions where the target transcript is not expressed in the tissue or cell line of interest. We test the method on a variety of miRNA transfection datasets and demonstrate increased accuracy versus generic miRNA target prediction methods.Availability and implementationFilTar is freely available and can be downloaded from https://github.com/TBradley27/FilTar. The tool is implemented using the Python and R programming languages, and is supported on GNU/Linux operating systems.Supplementary information Supplementary data are available at Bioinformatics online.

A novel computational approach to the silencing of Sugarcane Bacilliform Guadeloupe A Virus determines potential host-derived MicroRNAs in sugarcane (Saccharum officinarum L.).

Sugarcane Bacilliform Guadeloupe A Virus (SCBGAV, genus Badnavirus, family Caulimoviridae) is an emerging, deleterious pathogen of sugarcane which presents a substantial barrier to producing high sugarcane earnings. Sugarcane bacilliform viruses (SCBVs) are one of the main species that infect sugarcane. During the last 30 years, significant genetic changes in SCBV strains have been observed with a high risk of disease incidence associated with crop damage. SCBV infection may lead to significant losses in biomass production in susceptible sugarcane cultivars. The circular, double-stranded (ds) DNA genome of SCBGAV (7.4 Kb) is composed of three open reading frames (ORFs) on the positive strand that replicate by a reverse transcriptase. SCBGAV can infect sugarcane in a semipersistent manner via the insect vectors sugarcane mealybug species. In the current study, we used miRNA target prediction algorithms to identify and comprehensively analyze the genome-wide sugarcane (Saccharum officinarum L.)-encoded microRNA (miRNA) targets against the SCBGAV. Mature miRNA target sequences were retrieved from the miRBase (miRNA database) and were further analyzed for hybridization to the SCBGAV genome. Multiple computational approaches—including miRNA-target seed pairing, multiple target positions, minimum free energy, target site accessibility, maximum complementarity, pattern recognition and minimum folding energy for attachments—were considered by all algorithms. Among them, sof-miR396 was identified as the top effective candidate, capable of targeting the vital ORF3 of the SCBGAV genome. miRanda, RNA22 and RNAhybrid algorithms predicted hybridization of sof-miR396 at common locus position 3394. The predicted sugarcane miRNAs against viral mRNA targets possess antiviral activities, leading to translational inhibition by mRNA cleavage. Interaction network of sugarcane-encoded miRNAs with SCBGAV genes, created using Circos, allow analyze new targets. The finding of the present study acts as a first step towards the creation of SCBGAV-resistant sugarcane through the expression of the identified miRNAs.

MiR-200c sensitizes Olaparib-resistant ovarian cancer cells by targeting Neuropilin 1

BackgroundOvarian cancer (OC) is the most lethal gynecological malignancy and the second leading cause of cancer-related death in women. Treatment with PARP inhibitors (PARPi), such as Olaparib, has been recently introduced for OC patients, but resistance may occur and underlying mechanisms are still poorly understood. The aim of this study is to identify target genes within the tumor cells that might cause resistance to Olaparib. We focused on Neuropilin 1 (NRP1), a transmembrane receptor expressed in OC and correlated with poor survival, which has been also proposed as a key molecule in OC multidrug resistance.MethodsUsing three OC cell lines (UWB, UWB-BRCA and SKOV3) as model systems, we evaluated the biological and molecular effects of Olaparib on OC cell growth, cell cycle, DNA damage and apoptosis/autophagy induction, through MTT and colony forming assays, flow cytometry, immunofluorescence and Western blot analyses. We evaluated NRP1 expression in OC specimens and cell lines by Western blot and qRT-PCR, and used RNA interference to selectively inhibit NRP1. To identify miR-200c as a regulator of NRP1, we used miRNA target prediction algorithms and Pearsons’ correlation analysis in biopsies from OC patients. Then, we used a stable transfection approach to overexpress miR-200c in Olaparib-resistant cells.ResultsWe observed that NRP1 is expressed at high levels in resistant cells (SKOV3) and is upmodulated in partially sensitive cells (UWB-BRCA) upon prolonged Olaparib treatment, leading to poor drug response. Our results show that the selective inhibition of NRP1 is able to overcome Olaparib resistance in SKOV3 cells. Moreover, we demonstrated that miR-200c can target NRP1 in OC cells, causing its downmodulation, and that miR-200c overexpression is a valid approach to restore Olaparib sensitivity in OC resistant cells.ConclusionsThese data demonstrate that miR-200c significantly enhanced the anti-cancer efficacy of Olaparib in drug-resistant OC cells. Thus, the combination of Olaparib with miRNA-based therapy may represent a promising treatment for drug resistant OC, and our data may help in designing novel precision medicine trials for optimizing the clinical use of PARPi.